Table 4.

Prediction result of inhibition (IC₅₀) using SMILES to ECFP

Embedding method	Classification	Accuracy	Precision	Recall	F1
word2vec	LR	0.823	0.824	0.829	0.826
	LDA	0.823	0.831	0.818	0.824
	KNN	0.828	0.825	0.841	0.833
	CART	0.815	0.831	0.799	0.815
	NB	0.696	0.649	0.878	0.746
	SVM	0.830	0.829	0.841	0.834
	XGBoost	0.836	0.826	0.860	0.842
	RDForest	0.837	0.821	0.868	0.844
Ising-word2vec	LR	0.825	0.827	0.830	0.828
	LDA	0.830	0.835	0.829	0.832
	KNN	0.823	0.824	0.830	0.826
	CART	0.810	0.825	0.795	0.810
	NB	0.699	0.653	0.873	0.747
	SVM	0.832	0.830	0.842	0.836
	XGBoost	0.835	0.825	0.858	0.841
	RDForest	0.837	0.820	0.871	0.845